code: def power_transform_constraint(power):
      """Maps `s` to [-1 / power, inf)."""
  
      def constrain(x):
          if power == 0:
              return x
          return tf.math.softplus(x) - 1.0 / power
  
      return constrain
  
imports: import collections
  import inspect
  from absl import logging
  import hypothesis.strategies
  import tensorflow.compat.v2
  from tensorflow_probability.python import bijectors
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 10 for calling a global function with example usage: power_transform_constraint(power) and returns: constrain, unknown, x